Lossy/lossless region-of-interest image coding based on set partitioning in hierarchical trees

Eiji Atsumi, Nariman Farvardin

Research output: Contribution to conferencePaperpeer-review

Abstract

We have incorporated a Region-of-Interest (RoI) coding functionality into Said and Pearlman's SPIHT coding with integer transforms. By placing a higher emphasis on the transform coefficients pertaining to the RoI, the RoI is coded with higher fidelity than the rest of the image in earlier stages of progressive reconstruction, thus the 'important' part of the image is reconstructed more quickly than the rest of the image. This method significantly saves transmission time and storage space by terminating encoding or transmission in situations where the RoI needs to be coded losslessly and the rest of the image visually losslessly (lossy). In our model, the RoI can be flexibly specified either in the beginning or in the middle of the encoding process (either on the original image or on the full- or low-resolution image reconstructed by the decoder), through interaction with the user at the transmitting or the receiving end. Also, the speed with which the quality of the RoI improves in progressive decoding is flexibly specified by the user at either end. The proposed method is especially advantageous in an application where the image is browsed interactively, e.g. telemedicine.

Original languageEnglish
Pages87-91
Number of pages5
StatePublished - 1998
EventProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA
Duration: Oct 4 1998Oct 7 1998

Conference

ConferenceProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
CityChicago, IL, USA
Period10/4/9810/7/98

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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